FIA NLS Models: Biomass Growth vs. Stand Age – Additional Growth Estimators
JAH
2022-12-14
Background
This analysis document compliments FIA - NLS Models: Biomass Growth vs. Stand Age. All of the background information from that document applies to these analyses, which are extensions to them. The difference between that document and this analysis is the use of different growth estimators.
Here, we fit the models using: 1) calculated plot biomass growth (Mass-Balance method) using only trees >5 inches (12.5 cm) dbh (\(G_{MassBal > 5}\)), and 2) plot biomass growth (tree incremental growth method) for trees >5 inches (12.5 cm) dbh (\(G_{TI-NoIngrow}\)).
Below the model fitting procedure is implemented by ecoprovince:
Analysis 1: \(G_{MassBal > 5}\)
211 - Northeastern Mixed Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 6869 3003.0
## 2 6868 2999.0 1 4.02 9.2031 0.002425 **
## 3 6816 2317.2 52 681.73 38.5625 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 29089.03
## 2 2 29081.82
## 3 3 27199.38##
## Formula: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) *
## (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b *
## exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 1.135803 0.268134 4.236 2.31e-05 ***
## phi 0.014255 0.005449 2.616 0.00891 **
## alpha 0.183105 0.039688 4.614 4.03e-06 ***
## a 0.540533 0.168453 3.209 0.00134 **
## b 2.206353 0.192853 11.441 < 2e-16 ***
## c 52.447690 0.985862 53.200 < 2e-16 ***
## d 1.318388 0.086649 15.215 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5831 on 6816 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (54 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
predict and plot
plotting 2
212 - Laurentian Mixed Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 19351 10991.7
## 2 19346 10966.6 5 25.2 8.8747 1.989e-08 ***
## 3 18857 6831.3 489 4135.3 23.3433 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 82798.28
## 2 2 82741.70
## 3 3 72658.31##
## Formula: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) *
## (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b *
## exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 1.567865 0.223569 7.013 2.41e-12 ***
## phi 0.025003 0.003714 6.733 1.71e-11 ***
## alpha 0.184180 0.028101 6.554 5.74e-11 ***
## a 0.356236 0.022152 16.081 < 2e-16 ***
## b 1.777209 0.061579 28.860 < 2e-16 ***
## c 41.469035 0.427180 97.076 < 2e-16 ***
## d 1.238169 0.022233 55.691 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6019 on 18857 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (3851 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
predict and plot
## Warning: Removed 45 rows containing missing values (geom_point).
plotting 2
221 - Eastern Broadleaf Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 7319 3321.1
## 2 7318 3312.6 1 8.51 18.803 1.469e-05 ***
## 3 7254 2924.1 64 388.52 15.060 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 33832.56
## 2 2 33815.76
## 3 3 32720.09##
## Formula: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) *
## (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b *
## exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.74789 0.14029 -5.331 1.01e-07 ***
## phi 0.01983 0.00557 3.560 0.000374 ***
## alpha 0.54471 0.04161 13.090 < 2e-16 ***
## a 1.25134 0.46881 2.669 0.007620 **
## b 3.37115 0.47544 7.091 1.46e-12 ***
## c 46.48696 1.94765 23.868 < 2e-16 ***
## d 1.76805 0.21005 8.417 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6349 on 7254 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (72 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
predict and plot
## Warning: Removed 6 rows containing missing values (geom_point).
plotting 2
222 - Midwest Broadleaf Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 5044 2546.6
## 2 5043 2543.9 1 2.66 5.2805 0.02161 *
## 3 4823 1161.8 220 1382.14 26.0813 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 25129.16
## 2 2 25125.88
## 3 3 20632.07##
## Formula: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) *
## (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b *
## exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.13139 0.25293 -0.519 0.60345
## phi 0.03017 0.01011 2.984 0.00286 **
## alpha 0.40476 0.05142 7.872 4.27e-15 ***
## a 0.78330 0.11551 6.781 1.33e-11 ***
## b 2.69267 0.15975 16.856 < 2e-16 ***
## c 52.54274 1.61992 32.435 < 2e-16 ***
## d 1.34553 0.07458 18.041 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4908 on 4823 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (1015 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
predict and plot
## Warning: Removed 7 rows containing missing values (geom_point).
plotting 2
223 - Central Interior Broadleaf Forest
model selection 1
## Error in nls(fg2_MBg5, data = G_223, start = c(ge = ge.start, a = a.start, :
## parameters without starting value in 'data': phi
## model AIC
## 1 1 40473.24
## 2 2 NA
## 3 3 36463.41##
## Formula: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) *
## (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b *
## exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.467315 0.144891 -3.225 0.001263 **
## phi 0.000000 0.006509 0.000 1.000000
## alpha 0.375168 0.043377 8.649 < 2e-16 ***
## a 1.275827 0.341585 3.735 0.000189 ***
## b 2.573411 0.343780 7.486 7.81e-14 ***
## c 36.257429 1.192385 30.407 < 2e-16 ***
## d 1.480254 0.160021 9.250 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5338 on 8729 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (1274 observations deleted due to missingness)summary
- simple model: fits
- phi model: does not fit
- phi-alpha model: fits
plot residuals
predict and plot
## Warning: Removed 6 rows containing missing values (geom_point).
plotting 2
231 - Southeastern Mixed Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 13446 8033.9
## 2 13445 8027.2 1 6.66 11.1542 0.0008407 ***
## 3 13194 6846.6 251 1180.59 9.0641 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 69488.49
## 2 2 69479.34
## 3 3 66707.05##
## Formula: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) *
## (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b *
## exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 2.066238 0.236245 8.746 < 2e-16 ***
## phi 0.013774 0.004729 2.913 0.00359 **
## alpha 0.601642 0.022273 27.012 < 2e-16 ***
## a 0.682610 0.091980 7.421 1.23e-13 ***
## b 3.572651 0.149622 23.878 < 2e-16 ***
## c 24.576045 0.336579 73.017 < 2e-16 ***
## d 1.540009 0.044687 34.462 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7204 on 13194 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (316 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
predict and plot
## Warning: Removed 30 rows containing missing values (geom_point).
plotting 2
232 - Outer Coastal Plain Mixed Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 13504 9840.7
## 2 13503 9834.4 1 6.37 8.7513 0.003099 **
## 3 13220 9027.8 283 806.59 4.1737 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 69847.07
## 2 2 69840.31
## 3 3 67887.84##
## Formula: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) *
## (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b *
## exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 1.629451 0.242248 6.726 1.81e-11 ***
## phi 0.013328 0.005165 2.580 0.00988 **
## alpha 0.588401 0.022782 25.827 < 2e-16 ***
## a 0.545364 0.113742 4.795 1.65e-06 ***
## b 3.503712 0.168790 20.758 < 2e-16 ***
## c 23.685176 0.381675 62.056 < 2e-16 ***
## d 1.624809 0.055735 29.153 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.8264 on 13220 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (402 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
predict and plot
## Warning: Removed 66 rows containing missing values (geom_point).
plotting 2
234 - Lower Mississippi Riverine Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 1368 1225.98
## 2 1367 1225.97 1 0.008 0.0092 0.9237
## 3 1315 933.16 52 292.809 7.9351 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 7586.402
## 2 2 7588.393
## 3 3 7031.294##
## Formula: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) *
## (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b *
## exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 1.634e+00 1.274e+00 1.283 0.1998
## phi 3.623e-04 2.372e-02 0.015 0.9878
## alpha 7.134e-01 9.118e-02 7.823 1.05e-14 ***
## a 1.732e+00 1.590e+00 1.089 0.2764
## b 2.114e+00 1.596e+00 1.325 0.1854
## c 2.603e+01 3.658e+00 7.115 1.83e-12 ***
## d 1.541e+00 9.306e-01 1.656 0.0979 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.8424 on 1315 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (66 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits ### plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.89838, p-value < 2.2e-16
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -5.0397, p-value = 4.663e-07
## alternative hypothesis: two.sidedpredict and plot
## Warning: Removed 5 rows containing missing values (geom_point).
plotting 2
242 - Pacific Lowland Mixed Forest
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
251 - Prairie Parkland (Temperate)
model selection 1
## Analysis of Variance Table
##
## Model 1: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 1888 947.45
## 2 1887 947.45 1 0.00 0.000 1
## 3 1772 380.43 115 567.01 22.966 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 9343.582
## 2 2 9345.582
## 3 3 7301.476##
## Formula: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) *
## (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b *
## exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 0.79937 0.56065 1.426 0.15411
## phi 0.01272 0.01241 1.025 0.30529
## alpha 0.05465 0.10935 0.500 0.61729
## a 1.62452 0.35714 4.549 5.76e-06 ***
## b 0.97980 0.34828 2.813 0.00496 **
## c 40.36397 3.54417 11.389 < 2e-16 ***
## d 1.21487 0.37060 3.278 0.00107 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4633 on 1772 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (516 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.81073, p-value < 2.2e-16
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -7.8019, p-value = 6.099e-15
## alternative hypothesis: two.sidedpredict and plot
## Warning: Removed 2 rows containing missing values (geom_point).
plotting 2
255 - Prairie Parkland (Subtropical)
model selection 1
## Analysis of Variance Table
##
## Model 1: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 710 1183.68
## 2 709 1169.58 1 14.093 8.5431 0.003579 **
## 3 666 945.02 43 224.565 3.6805 3.542e-13 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 3587.653
## 2 2 3581.089
## 3 3 3319.214##
## Formula: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) *
## (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b *
## exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 0.63859 1.25611 0.508 0.611350
## phi 0.08964 0.03345 2.680 0.007544 **
## alpha 0.22908 0.22321 1.026 0.305122
## a 1.01818 0.30866 3.299 0.001023 **
## b 1.98761 0.55333 3.592 0.000352 ***
## c 23.95708 2.37494 10.087 < 2e-16 ***
## d 0.85191 0.18245 4.669 3.66e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.191 on 666 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (44 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.91339, p-value < 2.2e-16
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -5.1185, p-value = 3.08e-07
## alternative hypothesis: two.sidedpredict and plot
## Warning: Removed 2 rows containing missing values (geom_point).
plotting 2
261 - California Coastal Chaparral Forest and Shrub
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
262 - California Dry Steppe
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
263 - California Coastal Steppe - Mixed Forest and Redwood Forest
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
313 - Colorado Plateau Semi-Desert
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
315 - Southwest Plateau and Plains Dry Steppe and Shrub
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
321 - Chihuahuan Semi-Desert
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
322 - American Semidesert and Desert
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
331 - Great Plains/Palouse Dry Steppe
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
332 - Great Plains Steppe
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
341 - Intermountain Semi-desert & Desert
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
342 - Intermountain Semi-Desert
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
411 - Everglades
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
M211 - Adirondack-New England Mixed forest - Coniferous Forest - Alpine Meadow
model selection 1
## Analysis of Variance Table
##
## Model 1: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 6765 2158.6
## 2 6764 2155.4 1 3.189 10.008 0.001565 **
## 3 6740 2077.4 24 77.937 10.536 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 25640.90
## 2 2 25632.89
## 3 3 25350.55##
## Formula: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) *
## (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b *
## exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 2.020678 0.339061 5.960 2.66e-09 ***
## phi 0.014575 0.004934 2.954 0.00315 **
## alpha 0.191226 0.035348 5.410 6.52e-08 ***
## a 0.278919 0.108523 2.570 0.01019 *
## b 1.980364 0.146760 13.494 < 2e-16 ***
## c 58.303418 1.209829 48.191 < 2e-16 ***
## d 1.388516 0.073400 18.917 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5552 on 6740 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (25 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
predict and plot
plotting 2
M221 - Eastern Broadleaf Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 8308 4415.0
## 2 8307 4415.0 1 0.00 0.000 0.9998
## 3 8252 4106.1 55 308.95 11.289 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 40211.66
## 2 2 40213.66
## 3 3 39425.66##
## Formula: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) *
## (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b *
## exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 0.585873 0.212996 2.751 0.00596 **
## phi 0.000000 0.006393 0.000 1.00000
## alpha 0.581593 0.056019 10.382 < 2e-16 ***
## a 1.342455 0.462513 2.903 0.00371 **
## b 2.784604 0.461040 6.040 1.61e-09 ***
## c 33.907419 1.305147 25.980 < 2e-16 ***
## d 1.550452 0.205951 7.528 5.68e-14 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7054 on 8252 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (56 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
predict and plot
## Warning: Removed 2 rows containing missing values (geom_point).
plotting 2
M223 - Ozark Broadleaf Forest Meadow
model selection 1
## Analysis of Variance Table
##
## Model 1: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 890 500.00
## 2 889 500.00 1 0.0000 0.0000 1.0000
## 3 882 494.01 7 5.9895 1.5277 0.1542
## model AIC
## 1 1 3721.381
## 2 2 3723.381
## 3 3 3699.880##
## Formula: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) *
## (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b *
## exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 2.47372 1.44590 1.711 0.087460 .
## phi 0.00000 0.02552 0.000 1.000000
## alpha 0.39600 0.16041 2.469 0.013751 *
## a 1.54882 0.32376 4.784 2.01e-06 ***
## b 1.26860 0.36223 3.502 0.000485 ***
## c 29.68437 1.99852 14.853 < 2e-16 ***
## d 0.49984 0.10422 4.796 1.90e-06 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7484 on 882 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (7 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.94889, p-value < 2.2e-16
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -3.1798, p-value = 0.001474
## alternative hypothesis: two.sidedpredict and plot
plotting 2
M231 - Ouachita Mixed Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 1000 566.90
## 2 999 563.39 1 3.511 6.2249 0.01276 *
## 3 986 515.05 13 48.343 7.1190 2.222e-13 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 4308.841
## 2 2 4304.598
## 3 3 4182.594##
## Formula: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) *
## (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b *
## exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 2.34276 1.54565 1.516 0.129914
## phi 0.04332 0.02507 1.728 0.084294 .
## alpha 0.44951 0.11572 3.885 0.000109 ***
## a 0.00000 5.52454 0.000 1.000000
## b 2.01907 5.51282 0.366 0.714258
## c 26.31121 4.82682 5.451 6.33e-08 ***
## d 2.73767 4.45733 0.614 0.539229
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7227 on 986 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (13 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.94511, p-value < 2.2e-16
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -6.0956, p-value = 1.09e-09
## alternative hypothesis: two.sidedpredict and plot
plotting 2
M242 - Cascade Mixed Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 3140 2796.3
## 2 3139 2796.0 1 0.32 0.359 0.5491
## 3 3126 2660.4 13 135.63 12.259 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 17424.89
## 2 2 17426.53
## 3 3 17229.36##
## Formula: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) *
## (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b *
## exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -1.75073 0.27996 -6.253 4.56e-10 ***
## phi 0.03950 0.01826 2.164 0.0306 *
## alpha 0.95397 0.07539 12.653 < 2e-16 ***
## a 6.71695 0.64071 10.484 < 2e-16 ***
## b 5.31578 0.99635 5.335 1.02e-07 ***
## c 34.74904 1.57550 22.056 < 2e-16 ***
## d 0.32758 0.05318 6.160 8.21e-10 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9225 on 3126 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (91 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.92891, p-value < 2.2e-16
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -14.071, p-value < 2.2e-16
## alternative hypothesis: two.sidedpredict and plot
## Warning: Removed 14 rows containing missing values (geom_point).
plotting 2
M261 - Sierran Steppe - Mixed Forest - Coniferous Forest - Alpine Meadow
model selection 1
## Analysis of Variance Table
##
## Model 1: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 1681 625.59
## 2 1680 587.31 1 38.279 109.4970 < 2e-16 ***
## 3 1667 579.35 13 7.957 1.7612 0.04396 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 8778.340
## 2 2 8673.884
## 3 3 8607.333##
## Formula: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) *
## (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b *
## exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -2.00838 0.30608 -6.562 7.08e-11 ***
## phi 0.22025 0.01626 13.546 < 2e-16 ***
## alpha 0.51836 0.11645 4.451 9.09e-06 ***
## a 0.00000 9.48494 0.000 1.000
## b 9.21284 9.45565 0.974 0.330
## c 47.43124 8.60479 5.512 4.10e-08 ***
## d 2.78559 1.92378 1.448 0.148
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5895 on 1667 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (303 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.89324, p-value < 2.2e-16
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -0.95054, p-value = 0.3418
## alternative hypothesis: two.sidedpredict and plot
## Warning: Removed 9 rows containing missing values (geom_point).
plotting 2
M262 - Califormia Coastal Range = Coniferous Forest - Open woodland Shrub Meadow
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
M313 - Arizona-New Mexico Mountains Semi-Desert - Open Woodland - Coniferous Forest - Alpine Meadow
model selection 1
## Analysis of Variance Table
##
## Model 1: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 360 160.54
## 2 359 159.32 1 1.22705 2.7650 0.09722 .
## 3 358 158.77 1 0.54375 1.2261 0.26892
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 1023.403
## 2 2 1022.602
## 3 3 1023.355##
## Formula: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) *
## (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -2.15379 0.40652 -5.298 2.05e-07 ***
## phi 0.05231 0.02682 1.951 0.051867 .
## a 0.00000 5.22047 0.000 1.000000
## b 3.39430 5.29020 0.642 0.521529
## c 55.12209 16.07696 3.429 0.000677 ***
## d 1.96404 2.19982 0.893 0.372552
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6662 on 359 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (2 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.949, p-value = 6.568e-10
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -0.11276, p-value = 0.9102
## alternative hypothesis: two.sidedpredict and plot
plotting 2
M331 - Southern Rocky Mountain Steppe - Open Woodland - Coniferous Forest - Alpine Meadow
model selection 1
## Analysis of Variance Table
##
## Model 1: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 1736 1481.0
## 2 1735 1469.4 1 11.569 13.660 0.0002259 ***
## 3 1718 1335.2 17 134.204 10.157 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 5173.137
## 2 2 5161.484
## 3 3 4986.083##
## Formula: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) *
## (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b *
## exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.55586 0.66949 -0.830 0.406
## phi 0.07262 0.01548 4.690 2.94e-06 ***
## alpha 0.51606 0.06292 8.202 4.59e-16 ***
## a 0.77418 0.18762 4.126 3.86e-05 ***
## b 1.22747 0.23917 5.132 3.19e-07 ***
## c 65.00451 4.28144 15.183 < 2e-16 ***
## d 1.10731 0.15429 7.177 1.06e-12 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.8816 on 1718 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (31 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.85284, p-value < 2.2e-16
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -4.7205, p-value = 2.353e-06
## alternative hypothesis: two.sidedpredict and plot
## Warning: Removed 7 rows containing missing values (geom_point).
plotting 2
M332 - Middle Rocky Mountain Steppe - Coniferous Forest - Alpine Meadow
model selection 1
## Analysis of Variance Table
##
## Model 1: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 2527 1959.3
## 2 2526 1953.0 1 6.279 8.1215 0.00441 **
## 3 2484 1815.2 42 137.796 4.4896 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 9211.166
## 2 2 9205.038
## 3 3 9021.180##
## Formula: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) *
## (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b *
## exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.71450 0.54278 -1.316 0.1882
## phi 0.04659 0.01839 2.534 0.0113 *
## alpha 0.68943 0.05997 11.496 < 2e-16 ***
## a 0.64584 0.13706 4.712 2.59e-06 ***
## b 2.02783 0.30420 6.666 3.23e-11 ***
## c 80.25839 4.76324 16.850 < 2e-16 ***
## d 1.46671 0.12238 11.985 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.8548 on 2484 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (121 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.88181, p-value < 2.2e-16
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -5.4317, p-value = 5.582e-08
## alternative hypothesis: two.sidedpredict and plot
## Warning: Removed 28 rows containing missing values (geom_point).
plotting 2
M333 - Northern Rocky Mountain Steppe - Coniferous Forest - Alpine Meadow
model selection 1
## Analysis of Variance Table
##
## Model 1: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 1699 965.89
## 2 1698 964.53 1 1.359 2.3932 0.122
## 3 1669 879.04 29 85.494 5.5974 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 7044.476
## 2 2 7044.076
## 3 3 6861.430##
## Formula: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) *
## (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b *
## exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.29122 0.77522 -0.376 0.707
## phi 0.01886 0.02134 0.884 0.377
## alpha 0.74650 0.06311 11.829 < 2e-16 ***
## a 0.84169 0.19535 4.309 1.74e-05 ***
## b 3.16485 0.59477 5.321 1.17e-07 ***
## c 52.53802 1.86680 28.143 < 2e-16 ***
## d 1.28591 0.08224 15.636 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7257 on 1669 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (77 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.9217, p-value < 2.2e-16
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -4.5838, p-value = 4.566e-06
## alternative hypothesis: two.sidedpredict and plot
## Warning: Removed 14 rows containing missing values (geom_point).
plotting 2
M334 - Black Hills Coniferous Forest
model selection 1
## Error in nls(fg1_MBg5, data = G_M334, start = c(ge = ge.start, a = a.start, :
## Convergence failure: singular convergence (7)
## Error in nls(fg2_MBg5, data = G_M334, start = c(ge = ge.start, phi = phi.start, :
## Convergence failure: iteration limit reached without convergence (10)
## model AIC
## 1 1 NA
## 2 2 NA
## 3 3 1307.702##
## Formula: G_MassBal_g5_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) *
## (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b *
## exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -3.63950 0.11263 -32.312 < 2e-16 ***
## phi 0.07200 0.02858 2.520 0.012193 *
## alpha 0.68326 0.17569 3.889 0.000121 ***
## a 0.00000 56.36679 0.000 1.000000
## b 4.67839 56.15257 0.083 0.933648
## c 72.87014 25.79751 2.825 0.005005 **
## d 2.07779 14.63256 0.142 0.887164
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.4335 on 348 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (104 observations deleted due to missingness)summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.89611, p-value = 7.794e-15
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -4.1791, p-value = 2.926e-05
## alternative hypothesis: two.sidedpredict and plot
## Warning: Removed 1 rows containing missing values (geom_point).
plotting 2
M341 - Nevada-Utah Mountains Semi-Desert - Coniferous Forest - Alpine Meadow
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
Fitted parameters
Best / selected models by ecoprovince
| Code | Ecoregion | Sel.Mod |
|---|---|---|
| 211 | Northeastern Mixed Forest | 3 |
| 212 | Laurentian Mixed Forest | 3 |
| 221 | Eastern Broadleaf Forest | 3 |
| 222 | Midwest Broadleaf Forest | 3 |
| 223 | Central Interior Broadleaf Forest | 3 |
| 231 | Southeastern Mixed Forest | 3 |
| 232 | Outer Coastal Plain Mixed Forest | 3 |
| 234 | Lower Mississippi Riverine Forest | 3 |
| 242 | Pacific Lowland Mixed Forest | NA |
| 251 | Prairie Parkland (Temperate) | 3 |
| 255 | Prairie Parkland (Subtropical) | 3 |
| 261 | California Coastal Chaparral Forest and Shrub | NA |
| 262 | California Dry Steppe | NA |
| 263 | California Coastal Steppe - Mixed Forest and Redwood Forest | NA |
| 313 | Colorado Plateau Semi-Desert | NA |
| 315 | Southwest Plateau and Plains Dry Steppe and Shrub | NA |
| 321 | Chihuahuan Semi-Desert | NA |
| 322 | American Semidesert and Desert | NA |
| 331 | Great Plains/Palouse Dry Steppe | NA |
| 332 | Great Plains Steppe | NA |
| 341 | Intermountain Semi-Desert and Desert | NA |
| 342 | Intermountain Semi-Desert | NA |
| 411 | Everglades | NA |
| M211 | Adirondack-New England Mixed forest - Coniferous Forest - Alpine Meadow | 3 |
| M221 | Central Appalachian Broadleaf Forest - Coniferous Forest - Meadow | 3 |
| M223 | Ozark Broadleaf Forest Meadow | 3 |
| M231 | Ouachita Mixed Forest | 3 |
| M242 | Cascade Mixed Forest | 3 |
| M261 | Sierran Steppe - Mixed Forest - Coniferous Forest - Alpine Meadow | 3 |
| M262 | California Coastal Range Coniferous Forest - Open Woodland - Shrub - Meadow | NA |
| M313 | Arizona-New Mexico Mountains Semi-Desert - Open Woodland - Coniferous Forest - Alpine Meadow | 2 |
| M331 | Southern Rocky Mountain Steppe - Open Woodland - Coniferous Forest - Alpine Meadow | 3 |
| M332 | Middle Rocky Mountain Steppe - Coniferous Forest - Alpine Meadow | 3 |
| M333 | Northern Rocky Mountain Steppe - Coniferous Forest - Alpine Meadow | 3 |
| M334 | Black Hills Coniferous Forest | 3 |
| M341 | Nevada-Utah Mountains Semi-Desert - Coniferous Forest - Alpine Meadow | NA |
table by ecoprovince
| Code | Ecoregion | region | n.obs | n.plots | ge | ge.variance | ge.2.5 | ge.97.5 | phi | phi.variance | phi.2.5 | phi.97.5 | alpha | alpha.variance | alpha.2.5 | alpha.97.5 | a | a.2.5 | a.97.5 | b | b.2.5 | b.97.5 | c | c.2.5 | c.97.5 | d | d.2.5 | d.97.5 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 211 | Northeastern Mixed Forest | east | 6877 | 2876 | 1.1358026 | 0.0718957 | 0.6101767 | 1.6614285 | 0.0142553 | 0.0000297 | 0.0035740 | 0.0249365 | 0.1831049 | 0.0015752 | 0.1053031 | 0.2609067 | 0.5405335 | 0.2103135 | 0.8707534 | 2.2063530 | 1.8283002 | 2.584406 | 52.44769 | 50.51509 | 54.38029 | 1.3183883 | 1.1485289 | 1.4882478 |
| 212 | Laurentian Mixed Forest | east | 22715 | 9499 | 1.5678652 | 0.0499832 | 1.1296495 | 2.0060809 | 0.0250033 | 0.0000138 | 0.0177240 | 0.0322825 | 0.1841802 | 0.0007896 | 0.1291003 | 0.2392600 | 0.3562359 | 0.3128153 | 0.3996564 | 1.7772086 | 1.6565075 | 1.897910 | 41.46903 | 40.63172 | 42.30635 | 1.2381687 | 1.1945906 | 1.2817468 |
| 221 | Eastern Broadleaf Forest | east | 7333 | 3571 | -0.7478866 | 0.0196814 | -1.0228966 | -0.4728765 | 0.0198284 | 0.0000310 | 0.0089093 | 0.0307475 | 0.5447131 | 0.0017315 | 0.4631426 | 0.6262836 | 1.2513411 | 0.3323367 | 2.1703456 | 3.3711544 | 2.4391496 | 4.303159 | 46.48696 | 42.66900 | 50.30493 | 1.7680525 | 1.3562954 | 2.1798095 |
| 222 | Midwest Broadleaf Forest | east | 5845 | 2589 | -0.1313922 | 0.0639750 | -0.6272556 | 0.3644713 | 0.0301678 | 0.0001022 | 0.0103500 | 0.0499856 | 0.4047612 | 0.0026436 | 0.3039623 | 0.5055600 | 0.7833034 | 0.5568561 | 1.0097507 | 2.6926746 | 2.3794957 | 3.005854 | 52.54274 | 49.36696 | 55.71853 | 1.3455341 | 1.1993226 | 1.4917455 |
| 223 | Central Interior Broadleaf Forest | east | 10010 | 3864 | -0.4673151 | 0.0209933 | -0.7513347 | -0.1832956 | 0.0000000 | 0.0000424 | -0.0127589 | 0.0127589 | 0.3751680 | 0.0018816 | 0.2901389 | 0.4601971 | 1.2758269 | 0.6062395 | 1.9454142 | 2.5734109 | 1.8995209 | 3.247301 | 36.25743 | 33.92007 | 38.59478 | 1.4802542 | 1.1665750 | 1.7939333 |
| 231 | Southeastern Mixed Forest | east | 13517 | 6193 | 2.0662376 | 0.0558116 | 1.6031638 | 2.5293115 | 0.0137735 | 0.0000224 | 0.0045038 | 0.0230432 | 0.6016415 | 0.0004961 | 0.5579835 | 0.6452995 | 0.6826103 | 0.5023169 | 0.8629036 | 3.5726505 | 3.2793706 | 3.865930 | 24.57605 | 23.91630 | 25.23579 | 1.5400092 | 1.4524170 | 1.6276014 |
| 232 | Outer Coastal Plain Mixed Forest | east | 13629 | 6626 | 1.6294507 | 0.0586842 | 1.1546096 | 2.1042919 | 0.0133276 | 0.0000267 | 0.0032037 | 0.0234516 | 0.5884011 | 0.0005190 | 0.5437450 | 0.6330572 | 0.5453645 | 0.3224131 | 0.7683159 | 3.5037118 | 3.1728598 | 3.834564 | 23.68518 | 22.93704 | 24.43331 | 1.6248092 | 1.5155611 | 1.7340574 |
| 234 | Lower Mississippi Riverine Forest | east | 1388 | 778 | 1.6344890 | 1.6236070 | -0.8652143 | 4.1341923 | 0.0003623 | 0.0005627 | -0.0461744 | 0.0468989 | 0.7133628 | 0.0083146 | 0.5344799 | 0.8922456 | 1.7316791 | -1.3883318 | 4.8516900 | 2.1144852 | -1.0164079 | 5.245378 | 26.02657 | 18.85077 | 33.20237 | 1.5411483 | -0.2844287 | 3.3667253 |
| 242 | Pacific Lowland Mixed Forest | pacific | 83 | 83 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 251 | Prairie Parkland (Temperate) | east | 2295 | 906 | 0.7993703 | 0.3143340 | -0.3002443 | 1.8989849 | 0.0127219 | 0.0001539 | -0.0116103 | 0.0370541 | 0.0546507 | 0.0119575 | -0.1598183 | 0.2691198 | 1.6245155 | 0.9240594 | 2.3249716 | 0.9798006 | 0.2967198 | 1.662881 | 40.36397 | 33.41277 | 47.31517 | 1.2148696 | 0.4880126 | 1.9417266 |
| 255 | Prairie Parkland (Subtropical) | east | 717 | 319 | 0.6385901 | 1.5778126 | -1.8278227 | 3.1050028 | 0.0896379 | 0.0011187 | 0.0239636 | 0.1553122 | 0.2290813 | 0.0498229 | -0.2091997 | 0.6673623 | 1.0181837 | 0.4121230 | 1.6242444 | 1.9876145 | 0.9011419 | 3.074087 | 23.95708 | 19.29381 | 28.62035 | 0.8519050 | 0.4936622 | 1.2101478 |
| 261 | California Coastal Chaparral Forest and Shrub | pacific | 25 | 25 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 262 | California Dry Steppe | pacific | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 263 | California Coastal Steppe - Mixed Forest and Redwood Forest | pacific | 163 | 161 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 313 | Colorado Plateau Semi-Desert | interior west | 218 | 218 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 315 | Southwest Plateau and Plains Dry Steppe and Shrub | interior west | 4 | 4 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 321 | Chihuahuan Semi-Desert | interior west | 9 | 9 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 322 | American Semidesert and Desert | interior west | 3 | 3 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 331 | Great Plains/Palouse Dry Steppe | interior west | 331 | 255 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 332 | Great Plains Steppe | interior west | 232 | 128 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 341 | Intermountain Semi-Desert and Desert | interior west | 66 | 64 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 342 | Intermountain Semi-Desert | interior west | 124 | 123 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 411 | Everglades | east | 96 | 63 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M211 | Adirondack-New England Mixed forest - Coniferous Forest - Alpine Meadow | east | 6772 | 3006 | 2.0206783 | 0.1149621 | 1.3560124 | 2.6853443 | 0.0145752 | 0.0000243 | 0.0049025 | 0.0242479 | 0.1912260 | 0.0012495 | 0.1219334 | 0.2605185 | 0.2789192 | 0.0661806 | 0.4916579 | 1.9803640 | 1.6926687 | 2.268059 | 58.30342 | 55.93177 | 60.67507 | 1.3885158 | 1.2446280 | 1.5324036 |
| M221 | Central Appalachian Broadleaf Forest - Coniferous Forest - Meadow | east | 8315 | 3810 | 0.5858733 | 0.0453673 | 0.1683474 | 1.0033992 | 0.0000000 | 0.0000409 | -0.0125325 | 0.0125325 | 0.5815929 | 0.0031381 | 0.4717815 | 0.6914044 | 1.3424552 | 0.4358128 | 2.2490975 | 2.7846037 | 1.8808488 | 3.688359 | 33.90742 | 31.34900 | 36.46583 | 1.5504517 | 1.1467369 | 1.9541665 |
| M223 | Ozark Broadleaf Forest Meadow | east | 896 | 349 | 2.4737170 | 2.0906244 | -0.3640874 | 5.3115215 | 0.0000000 | 0.0006511 | -0.0500792 | 0.0500792 | 0.3960003 | 0.0257320 | 0.0811669 | 0.7108337 | 1.5488202 | 0.9133961 | 2.1842444 | 1.2685985 | 0.5576736 | 1.979523 | 29.68437 | 25.76196 | 33.60678 | 0.4998388 | 0.2952899 | 0.7043878 |
| M231 | Ouachita Mixed Forest | east | 1006 | 495 | 2.3427611 | 2.3890459 | -0.6903881 | 5.3759103 | 0.0433228 | 0.0006285 | -0.0058748 | 0.0925204 | 0.4495133 | 0.0133907 | 0.2224309 | 0.6765957 | 0.0000000 | -10.8412117 | 10.8412117 | 2.0190667 | -8.7991435 | 12.837277 | 26.31121 | 16.83919 | 35.78324 | 2.7376676 | -6.0092775 | 11.4846126 |
| M242 | Cascade Mixed Forest | pacific | 3224 | 3207 | -1.7507253 | 0.0783782 | -2.2996514 | -1.2017992 | 0.0395038 | 0.0003333 | 0.0037079 | 0.0752997 | 0.9539747 | 0.0056843 | 0.8061470 | 1.1018024 | 6.7169542 | 5.4606953 | 7.9732131 | 5.3157755 | 3.3622132 | 7.269338 | 34.74904 | 31.65991 | 37.83816 | 0.3275765 | 0.2233085 | 0.4318446 |
| M261 | Sierran Steppe - Mixed Forest - Coniferous Forest - Alpine Meadow | pacific | 1977 | 1807 | -2.0083777 | 0.0936842 | -2.6087169 | -1.4080385 | 0.2202471 | 0.0002644 | 0.1883558 | 0.2521384 | 0.5183634 | 0.0135602 | 0.2899633 | 0.7467635 | 0.0000000 | -18.6036428 | 18.6036428 | 9.2128439 | -9.3333568 | 27.759045 | 47.43124 | 30.55390 | 64.30858 | 2.7855897 | -0.9876905 | 6.5588698 |
| M262 | California Coastal Range Coniferous Forest - Open Woodland - Shrub - Meadow | interior west | 30 | 26 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M313 | Arizona-New Mexico Mountains Semi-Desert - Open Woodland - Coniferous Forest - Alpine Meadow | interior west | 367 | 367 | -2.1537882 | 0.1652590 | -2.9532493 | -1.3543271 | 0.0523140 | 0.0007192 | -0.0004255 | 0.1050534 | NA | NA | NA | NA | 0.0000000 | -10.2665361 | 10.2665361 | 3.3942993 | -7.0093791 | 13.797978 | 55.12209 | 23.50524 | 86.73894 | 1.9640393 | -2.3621063 | 6.2901849 |
| M331 | Southern Rocky Mountain Steppe - Open Woodland - Coniferous Forest - Alpine Meadow | interior west | 1756 | 1756 | -0.5558620 | 0.4482148 | -1.8689603 | 0.7572364 | 0.0726215 | 0.0002397 | 0.0422529 | 0.1029901 | 0.5160623 | 0.0039592 | 0.3926500 | 0.6394745 | 0.7741773 | 0.4061840 | 1.1421706 | 1.2274666 | 0.7583769 | 1.696556 | 65.00451 | 56.60712 | 73.40191 | 1.1073097 | 0.8046946 | 1.4099248 |
| M332 | Middle Rocky Mountain Steppe - Coniferous Forest - Alpine Meadow | interior west | 2612 | 2602 | -0.7144995 | 0.2946088 | -1.7788449 | 0.3498459 | 0.0465865 | 0.0003380 | 0.0105346 | 0.0826385 | 0.6894272 | 0.0035962 | 0.5718338 | 0.8070206 | 0.6458423 | 0.3770725 | 0.9146120 | 2.0278279 | 1.4313095 | 2.624346 | 80.25839 | 70.91806 | 89.59871 | 1.4667143 | 1.2267428 | 1.7066859 |
| M333 | Northern Rocky Mountain Steppe - Coniferous Forest - Alpine Meadow | interior west | 1753 | 1742 | -0.2912166 | 0.6009678 | -1.8117248 | 1.2292916 | 0.0188591 | 0.0004555 | -0.0230006 | 0.0607188 | 0.7465015 | 0.0039829 | 0.6227177 | 0.8702852 | 0.8416879 | 0.4585357 | 1.2248401 | 3.1648466 | 1.9982701 | 4.331423 | 52.53802 | 48.87651 | 56.19953 | 1.2859073 | 1.1245978 | 1.4472168 |
| M334 | Black Hills Coniferous Forest | interior west | 459 | 181 | -3.6394992 | 0.0126865 | -3.8610292 | -3.4179693 | 0.0720006 | 0.0008165 | 0.0157986 | 0.1282026 | 0.6832624 | 0.0308657 | 0.3377219 | 1.0288030 | 0.0000000 | -110.8624479 | 110.8624479 | 4.6783912 | -105.7627115 | 115.119494 | 72.87014 | 22.13149 | 123.60879 | 2.0777924 | -26.7015797 | 30.8571645 |
| M341 | Nevada-Utah Mountains Semi-Desert - Coniferous Forest - Alpine Meadow | interior west | 220 | 220 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
plot ge
map
## OGR data source with driver: ESRI Shapefile
## Source: "C:\Users\hogan.jaaron\Dropbox\FIA_R\Mapping\S_USA.EcoMapProvinces\S_USA.EcoMapProvinces.shp", layer: "S_USA.EcoMapProvinces"
## with 37 features
## It has 17 fields
## Integer64 fields read as strings: PROVINCE_ PROVINCE_I## Warning: package 'ggnewscale' was built under R version 4.2.1## Warning in grid.Call(C_stringMetric, as.graphicsAnnot(x$label)): font family not
## found in Windows font database
## Warning in grid.Call(C_stringMetric, as.graphicsAnnot(x$label)): font family not
## found in Windows font database## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, : font
## family not found in Windows font database
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, : font
## family not found in Windows font database
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, : font
## family not found in Windows font database
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, : font
## family not found in Windows font database
plot phi (effect of DeltaPDSI)
plot alpha (biomass growth compensation effect)
plot a coefficient
## Warning: Removed 15 rows containing missing values (geom_point).
plot b coefficient
## Warning: Removed 15 rows containing missing values (geom_point).
plot c coefficient
## Warning: Removed 1 rows containing missing values (geom_hline).## Warning: Removed 16 rows containing missing values (geom_point).
plot d coefficient
## Warning: Removed 15 rows containing missing values (geom_point).
Caclulations - weighted averages
ge (stand biomass growth enhancement factor in % 2000-2021)
## region weighted.ge weighted.ge.std_Error 95 % CI, upper 95 % CI, lower
## 1 entire US 0.61164549 0.07927918 0.767032675 0.4562583
## 2 pacific -0.15958074 0.01820490 -0.123899140 -0.1952623
## 3 east 0.85394889 0.06631074 0.983917935 0.7239799
## 4 interior west -0.08272266 0.03945448 -0.005391883 -0.1600534phi (effect of DeltaPDSI)
## region weighted.phi weighted.phi.std_Error 95 % CI, upper
## 1 entire US 0.026675612 0.002162048 0.030913227
## 2 pacific 0.009057837 0.001130894 0.011274389
## 3 east 0.012199987 0.001429816 0.015002426
## 4 interior west 0.005417788 0.001162393 0.007696079
## 95 % CI, lower
## 1 0.022437998
## 2 0.006841284
## 3 0.009397549
## 4 0.003139497alpha (biomass growth compensation effect)
## region weighted.alpha weighted.alpha.std_Error 95 % CI, upper
## 1 entire US 0.45391179 0.011314723 0.47608865
## 2 pacific 0.06898713 0.005533544 0.07983288
## 3 east 0.31372619 0.009088688 0.33154002
## 4 interior west 0.07119846 0.003846895 0.07873838
## 95 % CI, lower
## 1 0.43173493
## 2 0.05814139
## 3 0.29591237
## 4 0.06365855Analaysis 2: \(G_{TI-NoIngrow}\)
211 - Northeastern Mixed Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 6869 3216.6
## 2 6868 3216.5 1 0.056 0.1204 0.7286
## 3 6816 3000.9 52 215.657 9.4199 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 24882.32
## 2 2 24884.20
## 3 3 24355.03##
## Formula: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) *
## ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) *
## (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 1.051904 0.287972 3.653 0.000261 ***
## phi 0.006179 0.005892 1.049 0.294374
## alpha 0.836251 0.038662 21.630 < 2e-16 ***
## a 0.504459 0.045721 11.033 < 2e-16 ***
## b 1.844700 0.097873 18.848 < 2e-16 ***
## c 68.869770 1.253421 54.945 < 2e-16 ***
## d 0.974340 0.037853 25.740 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6635 on 6816 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (54 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
predict and plot
## Warning: Removed 1 rows containing missing values (geom_point).
plotting 2
212 - Laurentian Mixed Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 19351 23127
## 2 19346 23042 5 84.74 14.2293 6.28e-14 ***
## 3 18857 21019 489 2023.12 3.7117 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 63998.00
## 2 2 63917.40
## 3 3 61608.95##
## Formula: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) *
## ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) *
## (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 1.083416 0.220332 4.917 8.85e-07 ***
## phi 0.036821 0.004243 8.679 < 2e-16 ***
## alpha 1.042066 0.026868 38.785 < 2e-16 ***
## a 0.301247 0.013973 21.559 < 2e-16 ***
## b 1.351310 0.048031 28.134 < 2e-16 ***
## c 61.261958 0.812407 75.408 < 2e-16 ***
## d 1.023659 0.020133 50.844 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.056 on 18857 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (3851 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
predict and plot
## Warning: Removed 40 rows containing missing values (geom_point).
plotting 2
221 - Eastern Broadleaf Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 7319 3643.2
## 2 7318 3639.8 1 3.46 6.9571 0.008366 **
## 3 7254 3430.7 64 209.12 6.9091 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 31554.54
## 2 2 31549.58
## 3 3 30985.52##
## Formula: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) *
## ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) *
## (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.762389 0.148296 -5.141 2.80e-07 ***
## phi 0.015255 0.005847 2.609 0.0091 **
## alpha 0.846238 0.042069 20.116 < 2e-16 ***
## a 0.952663 0.185209 5.144 2.76e-07 ***
## b 3.045339 0.207132 14.702 < 2e-16 ***
## c 62.842867 2.659028 23.634 < 2e-16 ***
## d 1.503863 0.115430 13.028 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6877 on 7254 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (72 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
predict and plot
## Warning: Removed 4 rows containing missing values (geom_point).
plotting 2
222 - Midwest Broadleaf Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 5044 4308.4
## 2 5043 4303.7 1 4.75 5.567 0.01834 *
## 3 4823 3732.6 220 571.06 3.354 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 19723.24
## 2 2 19719.67
## 3 3 18603.89##
## Formula: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) *
## ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) *
## (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.08175 0.28217 -0.29 0.77206
## phi 0.02831 0.01093 2.59 0.00963 **
## alpha 0.99507 0.04935 20.16 < 2e-16 ***
## a 0.61151 0.05628 10.87 < 2e-16 ***
## b 2.30415 0.12387 18.60 < 2e-16 ***
## c 63.30978 1.66568 38.01 < 2e-16 ***
## d 1.05644 0.04900 21.56 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.8797 on 4823 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (1015 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
predict and plot
## Warning: Removed 8 rows containing missing values (geom_point).
plotting 2
223 - Central Interior Broadleaf Forest
model selection 1
## Error in nls(fg2_TI, data = G_223, start = c(ge = ge.start, a = a.start, :
## parameters without starting value in 'data': phi
## model AIC
## 1 1 34828.86
## 2 2 NA
## 3 3 34003.35##
## Formula: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) *
## ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) *
## (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.803798 0.137371 -5.851 5.05e-09 ***
## phi 0.000000 0.007125 0.000 1
## alpha 0.757366 0.044133 17.161 < 2e-16 ***
## a 0.853571 0.172881 4.937 8.07e-07 ***
## b 2.441732 0.182297 13.394 < 2e-16 ***
## c 50.681798 1.212794 41.789 < 2e-16 ***
## d 1.302611 0.090146 14.450 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.8075 on 8729 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (1274 observations deleted due to missingness)summary
- simple model: fits
- phi model: does not fit
- phi-alpha model: fits
plot residuals
predict and plot
## Warning: Removed 5 rows containing missing values (geom_point).
plotting 2
231 - Southeastern Mixed Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 13446 12254
## 2 13445 12246 1 7.41 8.1354 0.004348 **
## 3 13194 11030 251 1215.95 5.7947 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 66367.52
## 2 2 66361.38
## 3 3 64655.63##
## Formula: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) *
## ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) *
## (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 1.605908 0.253031 6.347 2.27e-10 ***
## phi 0.014040 0.005778 2.430 0.0151 *
## alpha 0.944623 0.025460 37.102 < 2e-16 ***
## a 0.478924 0.031667 15.124 < 2e-16 ***
## b 3.166561 0.128340 24.673 < 2e-16 ***
## c 34.289511 0.518135 66.179 < 2e-16 ***
## d 1.275092 0.026627 47.887 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9143 on 13194 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (316 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
predict and plot
## Warning: Removed 27 rows containing missing values (geom_point).
plotting 2
232 - Outer Coastal Plain Mixed Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 13504 15331
## 2 13503 15316 1 15.08 13.2932 0.0002674 ***
## 3 13220 13788 283 1527.57 5.1754 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 65934.14
## 2 2 65922.84
## 3 3 64075.10##
## Formula: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) *
## ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) *
## (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 1.139737 0.245775 4.637 3.56e-06 ***
## phi 0.019881 0.006102 3.258 0.00112 **
## alpha 0.963979 0.024979 38.592 < 2e-16 ***
## a 0.411257 0.035530 11.575 < 2e-16 ***
## b 3.029624 0.129878 23.327 < 2e-16 ***
## c 32.680017 0.527000 62.011 < 2e-16 ***
## d 1.308955 0.029869 43.824 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.021 on 13220 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (402 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
predict and plot
## Warning: Removed 57 rows containing missing values (geom_point).
plotting 2
234 - Lower Mississippi Riverine Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 1368 2135.0
## 2 1367 2132.6 1 2.374 1.5216 0.2176
## 3 1315 1973.4 52 159.159 2.0395 2.556e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 7497.623
## 2 2 7498.096
## 3 3 7292.351##
## Formula: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) *
## ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) *
## (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.97717 0.58433 -1.672 0.09470 .
## phi 0.09904 0.03555 2.786 0.00541 **
## alpha 0.91559 0.12085 7.576 6.68e-14 ***
## a 1.33887 0.29741 4.502 7.33e-06 ***
## b 3.66786 0.63036 5.819 7.44e-09 ***
## c 42.96174 3.79018 11.335 < 2e-16 ***
## d 1.10915 0.18070 6.138 1.10e-09 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.225 on 1315 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (66 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits ### plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.85289, p-value < 2.2e-16
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -4.6124, p-value = 3.98e-06
## alternative hypothesis: two.sidedpredict and plot
## Warning: Removed 2 rows containing missing values (geom_point).
plotting 2
242 - Pacific Lowland Mixed Forest
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
251 - Prairie Parkland (Temperate)
model selection 1
## Analysis of Variance Table
##
## Model 1: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 1888 1534.7
## 2 1887 1533.9 1 0.786 0.9664 0.3257
## 3 1772 1348.7 115 185.236 2.1163 2.841e-10 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 6937.884
## 2 2 6938.914
## 3 3 6461.892##
## Formula: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) *
## ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) *
## (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 0.991649 0.608307 1.630 0.103
## phi 0.002689 0.012481 0.215 0.829
## alpha 0.494173 0.103537 4.773 1.96e-06 ***
## a 0.750331 0.166810 4.498 7.30e-06 ***
## b 1.354466 0.204618 6.619 4.76e-11 ***
## c 55.232328 2.635890 20.954 < 2e-16 ***
## d 1.117919 0.139079 8.038 1.65e-15 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.8724 on 1772 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (516 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.90525, p-value < 2.2e-16
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -10.713, p-value < 2.2e-16
## alternative hypothesis: two.sidedpredict and plot
## Warning: Removed 9 rows containing missing values (geom_point).
plotting 2
255 - Prairie Parkland (Subtropical)
model selection 1
## Analysis of Variance Table
##
## Model 1: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 710 3128.3
## 2 709 3093.4 1 34.963 8.0136 0.004774 **
## 3 666 2994.5 43 98.892 0.5115 0.996202
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 3570.774
## 2 2 3564.738
## 3 3 3509.035##
## Formula: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) *
## ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) *
## (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 3.89797 4.96252 0.785 0.43245
## phi 0.16636 0.05922 2.809 0.00511 **
## alpha 0.22739 0.37758 0.602 0.54723
## a 0.15024 0.09137 1.644 0.10061
## b 1.03213 0.61042 1.691 0.09133 .
## c 29.91856 2.76638 10.815 < 2e-16 ***
## d 0.87522 0.15129 5.785 1.12e-08 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 2.12 on 666 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (44 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.9002, p-value < 2.2e-16
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -5.2453, p-value = 1.561e-07
## alternative hypothesis: two.sidedpredict and plot
plotting 2
261 - California Coastal Chaparral Forest and Shrub
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
262 - California Dry Steppe
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
263 - California Coastal Steppe - Mixed Forest and Redwood Forest
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
313 - Colorado Plateau Semi-Desert
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
315 - Southwest Plateau and Plains Dry Steppe and Shrub
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
321 - Chihuahuan Semi-Desert
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
322 - American Semidesert and Desert
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
331 - Great Plains/Palouse Dry Steppe
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
332 - Great Plains Steppe
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
341 - Intermountain Semi-desert & Desert
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
342 - Intermountain Semi-Desert
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
411 - Everglades
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
M211 - Adirondack-New England Mixed forest - Coniferous Forest - Alpine Meadow
model selection 1
## Analysis of Variance Table
##
## Model 1: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 6765 3120.3
## 2 6764 3111.3 1 9.075 19.729 9.066e-06 ***
## 3 6740 2905.7 24 205.555 19.867 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 23241.99
## 2 2 23224.27
## 3 3 22758.44##
## Formula: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) *
## ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) *
## (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 1.530710 0.344829 4.439 9.18e-06 ***
## phi 0.021453 0.005869 3.655 0.000259 ***
## alpha 0.822003 0.035969 22.853 < 2e-16 ***
## a 0.256549 0.035128 7.303 3.13e-13 ***
## b 1.715201 0.103495 16.573 < 2e-16 ***
## c 74.557987 1.725691 43.205 < 2e-16 ***
## d 1.085542 0.039201 27.692 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6566 on 6740 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (25 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
predict and plot
plotting 2
M221 - Eastern Broadleaf Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 8308 4928.4
## 2 8307 4928.4 1 0.00 0.0000 1
## 3 8252 4767.3 55 161.05 5.0684 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 37694.53
## 2 2 37696.53
## 3 3 37287.40##
## Formula: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) *
## ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) *
## (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 1.173351 0.275774 4.255 2.12e-05 ***
## phi 0.000000 0.006795 0.000 1
## alpha 0.905989 0.057344 15.799 < 2e-16 ***
## a 0.672806 0.162564 4.139 3.53e-05 ***
## b 2.343638 0.191092 12.264 < 2e-16 ***
## c 47.556263 1.190460 39.948 < 2e-16 ***
## d 1.374358 0.091086 15.089 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7601 on 8252 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (56 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
predict and plot
## Warning: Removed 2 rows containing missing values (geom_point).
plotting 2
M223 - Ozark Broadleaf Forest Meadow
model selection 1
## Analysis of Variance Table
##
## Model 1: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 890 702.27
## 2 889 702.27 1 0.000 0.0000 0.9999882
## 3 882 680.17 7 22.094 4.0928 0.0001961 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 3537.006
## 2 2 3539.006
## 3 3 3505.262##
## Formula: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) *
## ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) *
## (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 4.23213 2.58117 1.640 0.10144
## phi 0.00000 0.02955 0.000 1.00000
## alpha 1.00897 0.17368 5.809 8.76e-09 ***
## a 0.00000 0.25140 0.000 1.00000
## b 1.31904 0.44853 2.941 0.00336 **
## c 42.48170 2.77050 15.334 < 2e-16 ***
## d 1.27733 0.25380 5.033 5.86e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.8782 on 882 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (7 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.96657, p-value = 2.1e-13
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -3.1895, p-value = 0.001425
## alternative hypothesis: two.sidedpredict and plot
plotting 2
M231 - Ouachita Mixed Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 1000 894.75
## 2 999 888.75 1 5.991 6.7337 0.0095995 **
## 3 986 853.58 13 35.172 3.1252 0.0001365 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 4182.168
## 2 2 4177.416
## 3 3 4124.944##
## Formula: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) *
## ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) *
## (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 3.39959 2.57363 1.321 0.1868
## phi 0.05633 0.03145 1.791 0.0736 .
## alpha 0.82574 0.13610 6.067 1.85e-09 ***
## a 0.00000 0.33600 0.000 1.0000
## b 1.36576 0.53765 2.540 0.0112 *
## c 46.69611 5.96158 7.833 1.23e-14 ***
## d 1.75435 0.43638 4.020 6.26e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9304 on 986 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (13 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.93331, p-value < 2.2e-16
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -6.7781, p-value = 1.218e-11
## alternative hypothesis: two.sidedpredict and plot
plotting 2
M242 - Cascade Mixed Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 3140 2906.2
## 2 3139 2906.2 1 0.00 0.000 1
## 3 3126 2741.5 13 164.71 14.446 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 16154.59
## 2 2 16156.59
## 3 3 15944.25##
## Formula: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) *
## ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) *
## (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -1.69012 0.28448 -5.941 3.14e-09 ***
## phi 0.01996 0.01842 1.084 0.27855
## alpha 1.07660 0.07203 14.947 < 2e-16 ***
## a 0.00000 2.13763 0.000 1.00000
## b 6.23192 2.18152 2.857 0.00431 **
## c 94.67459 6.83750 13.846 < 2e-16 ***
## d 2.47547 0.59713 4.146 3.48e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9365 on 3126 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (91 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.9091, p-value < 2.2e-16
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -13.884, p-value < 2.2e-16
## alternative hypothesis: two.sidedpredict and plot
## Warning: Removed 17 rows containing missing values (geom_point).
plotting 2
M261 - Sierran Steppe - Mixed Forest - Coniferous Forest - Alpine Meadow
model selection 1
## Analysis of Variance Table
##
## Model 1: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 1681 1785.5
## 2 1680 1696.7 1 88.808 87.9362 < 2.2e-16 ***
## 3 1667 1639.5 13 57.180 4.4723 1.565e-07 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 7935.257
## 2 2 7851.239
## 3 3 7752.077##
## Formula: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) *
## ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) *
## (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -2.00185 0.29365 -6.817 1.29e-11 ***
## phi 0.19755 0.01621 12.190 < 2e-16 ***
## alpha 0.85077 0.10568 8.051 1.55e-15 ***
## a 2.93799 2.07549 1.416 0.15709
## b 4.95009 2.04338 2.422 0.01552 *
## c 49.61092 8.44463 5.875 5.10e-09 ***
## d 1.77705 0.67708 2.625 0.00875 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9917 on 1667 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (303 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.92265, p-value < 2.2e-16
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -2.2743, p-value = 0.02295
## alternative hypothesis: two.sidedpredict and plot
## Warning: Removed 10 rows containing missing values (geom_point).
plotting 2
M262 - Califormia Coastal Range = Coniferous Forest - Open woodland Shrub Meadow
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
M313 - Arizona-New Mexico Mountains Semi-Desert - Open Woodland - Coniferous Forest - Alpine Meadow
model selection 1
## Analysis of Variance Table
##
## Model 1: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 360 195.96
## 2 359 192.66 1 3.2997 6.1486 0.013610 *
## 3 358 187.44 1 5.2135 9.9573 0.001738 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 988.1197
## 2 2 983.9212
## 3 3 975.9079##
## Formula: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) *
## ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) *
## (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -2.50496 0.32713 -7.657 1.79e-13 ***
## phi 0.05300 0.03034 1.747 0.081532 .
## alpha 0.56839 0.16252 3.497 0.000529 ***
## a 0.00000 2.13594 0.000 1.000000
## b 3.59723 2.24022 1.606 0.109210
## c 67.83177 13.21943 5.131 4.73e-07 ***
## d 1.66097 0.89415 1.858 0.064047 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7236 on 358 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (2 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.93652, p-value = 2.287e-11
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -2.0261, p-value = 0.04275
## alternative hypothesis: two.sidedpredict and plot
## Warning: Removed 1 rows containing missing values (geom_point).
plotting 2
M331 - Southern Rocky Mountain Steppe - Open Woodland - Coniferous Forest - Alpine Meadow
model selection 1
## Analysis of Variance Table
##
## Model 1: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 1736 1676.4
## 2 1735 1662.8 1 13.595 14.1858 0.0001711 ***
## 3 1718 1540.4 17 122.428 8.0321 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 4364.968
## 2 2 4352.791
## 3 3 4221.416##
## Formula: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) *
## ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) *
## (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 0.62425 1.16195 0.537 0.591
## phi 0.08324 0.01580 5.270 1.54e-07 ***
## alpha 0.76591 0.05979 12.810 < 2e-16 ***
## a 0.48403 0.11880 4.074 4.82e-05 ***
## b 0.76035 0.17728 4.289 1.89e-05 ***
## c 82.23818 4.81492 17.080 < 2e-16 ***
## d 0.89016 0.10097 8.816 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9469 on 1718 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (31 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.88198, p-value < 2.2e-16
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -4.2914, p-value = 1.775e-05
## alternative hypothesis: two.sidedpredict and plot
## Warning: Removed 11 rows containing missing values (geom_point).
plotting 2
M332 - Middle Rocky Mountain Steppe - Coniferous Forest - Alpine Meadow
model selection 1
## Analysis of Variance Table
##
## Model 1: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 2527 2344.7
## 2 2526 2335.0 1 9.70 10.4936 0.001213 **
## 3 2484 2108.9 42 226.01 6.3381 < 2.2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 8552.063
## 2 2 8543.566
## 3 3 8318.048##
## Formula: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) *
## ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) *
## (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -0.83807 0.50931 -1.646 0.09999 .
## phi 0.05563 0.01810 3.074 0.00214 **
## alpha 0.95007 0.05611 16.933 < 2e-16 ***
## a 0.51222 0.08760 5.847 5.66e-09 ***
## b 2.11381 0.29325 7.208 7.48e-13 ***
## c 89.98718 4.03032 22.328 < 2e-16 ***
## d 1.24548 0.07416 16.794 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9214 on 2484 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (121 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.86768, p-value < 2.2e-16
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -4.7153, p-value = 2.413e-06
## alternative hypothesis: two.sidedpredict and plot
## Warning: Removed 22 rows containing missing values (geom_point).
plotting 2
M333 - Northern Rocky Mountain Steppe - Coniferous Forest - Alpine Meadow
model selection 1
## Analysis of Variance Table
##
## Model 1: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 1699 1220.6
## 2 1698 1220.3 1 0.32 0.4458 0.5044
## 3 1669 1059.1 29 161.22 8.7611 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 6534.582
## 2 2 6536.134
## 3 3 6297.177##
## Formula: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) *
## ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) *
## (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge 0.844464 1.264188 0.668 0.504
## phi 0.008227 0.022153 0.371 0.710
## alpha 0.977482 0.061116 15.994 < 2e-16 ***
## a 0.465264 0.114098 4.078 4.76e-05 ***
## b 2.367204 0.556112 4.257 2.19e-05 ***
## c 63.959874 1.887481 33.886 < 2e-16 ***
## d 1.082996 0.046847 23.118 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7966 on 1669 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (77 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.91308, p-value < 2.2e-16
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -5.8994, p-value = 3.647e-09
## alternative hypothesis: two.sidedpredict and plot
## Warning: Removed 15 rows containing missing values (geom_point).
plotting 2
M334 - Black Hills Coniferous Forest
model selection 1
## Analysis of Variance Table
##
## Model 1: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 2: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Model 3: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) * ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) * (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
## Res.Df Res.Sum Sq Df Sum Sq F value Pr(>F)
## 1 357 618.39
## 2 356 618.17 1 0.215 0.1239 0.72507
## 3 348 584.57 8 33.604 2.5006 0.01188 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## model AIC
## 1 1 1072.454
## 2 2 1074.328
## 3 3 1044.319##
## Formula: G_obs_TreeInc_NoIngrow_MgHaYr ~ (1 + (MEASTIME_avg - 1990) *
## ge/100) * (1 + phi * DeltaPDSI) * (1 - alpha * B_L_prop) *
## (a + b * exp(-((log(STDAGE_t1/c))/d)^2))
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## ge -1.19519 1.41779 -0.843 0.400
## phi 0.00000 0.04476 0.000 1.000
## alpha 0.68660 0.16773 4.093 5.29e-05 ***
## a 0.00000 7.85050 0.000 1.000
## b 1.40538 7.82290 0.180 0.858
## c 125.20338 121.81266 1.028 0.305
## d 2.50306 9.55036 0.262 0.793
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.296 on 348 degrees of freedom
##
## Algorithm "port", convergence message: relative convergence (4)
## (104 observations deleted due to missingness)summary
- simple model: fits
- phi model: fits
- phi-alpha model: fits
plot residuals
##
## ------
## Shapiro-Wilk normality test
##
## data: stdres
## W = 0.96219, p-value = 6.081e-08
##
##
## ------##
## Runs Test
##
## data: as.factor(run)
## Standard Normal = -3.952, p-value = 7.749e-05
## alternative hypothesis: two.sidedpredict and plot
## Warning: Removed 4 rows containing missing values (geom_point).
plotting 2
M341 - Nevada-Utah Mountains Semi-Desert - Coniferous Forest - Alpine Meadow
model selection 1
summary
- simple model: does not fit
- phi model: does not fit
- phi-alpha model: does not fit
plot residuals
## [1] "cannot plot residuals"predict and plot
## [1] "cannot plot data with prediction"plotting 2
Fitted parameters
Best / selected models by ecoprovince
| Code | Ecoregion | Sel.Mod |
|---|---|---|
| 211 | Northeastern Mixed Forest | 3 |
| 212 | Laurentian Mixed Forest | 3 |
| 221 | Eastern Broadleaf Forest | 3 |
| 222 | Midwest Broadleaf Forest | 3 |
| 223 | Central Interior Broadleaf Forest | 3 |
| 231 | Southeastern Mixed Forest | 3 |
| 232 | Outer Coastal Plain Mixed Forest | 3 |
| 234 | Lower Mississippi Riverine Forest | 3 |
| 242 | Pacific Lowland Mixed Forest | NA |
| 251 | Prairie Parkland (Temperate) | 3 |
| 255 | Prairie Parkland (Subtropical) | 3 |
| 261 | California Coastal Chaparral Forest and Shrub | NA |
| 262 | California Dry Steppe | NA |
| 263 | California Coastal Steppe - Mixed Forest and Redwood Forest | NA |
| 313 | Colorado Plateau Semi-Desert | NA |
| 315 | Southwest Plateau and Plains Dry Steppe and Shrub | NA |
| 321 | Chihuahuan Semi-Desert | NA |
| 322 | American Semidesert and Desert | NA |
| 331 | Great Plains/Palouse Dry Steppe | NA |
| 332 | Great Plains Steppe | NA |
| 341 | Intermountain Semi-Desert and Desert | NA |
| 342 | Intermountain Semi-Desert | NA |
| 411 | Everglades | NA |
| M211 | Adirondack-New England Mixed forest - Coniferous Forest - Alpine Meadow | 3 |
| M221 | Central Appalachian Broadleaf Forest - Coniferous Forest - Meadow | 3 |
| M223 | Ozark Broadleaf Forest Meadow | 3 |
| M231 | Ouachita Mixed Forest | 3 |
| M242 | Cascade Mixed Forest | 3 |
| M261 | Sierran Steppe - Mixed Forest - Coniferous Forest - Alpine Meadow | 3 |
| M262 | California Coastal Range Coniferous Forest - Open Woodland - Shrub - Meadow | NA |
| M313 | Arizona-New Mexico Mountains Semi-Desert - Open Woodland - Coniferous Forest - Alpine Meadow | 3 |
| M331 | Southern Rocky Mountain Steppe - Open Woodland - Coniferous Forest - Alpine Meadow | 3 |
| M332 | Middle Rocky Mountain Steppe - Coniferous Forest - Alpine Meadow | 3 |
| M333 | Northern Rocky Mountain Steppe - Coniferous Forest - Alpine Meadow | 3 |
| M334 | Black Hills Coniferous Forest | 3 |
| M341 | Nevada-Utah Mountains Semi-Desert - Coniferous Forest - Alpine Meadow | NA |
table by ecoprovince
| Code | Ecoregion | region | n.obs | n.plots | ge | ge.variance | ge.2.5 | ge.97.5 | phi | phi.variance | phi.2.5 | phi.97.5 | alpha | alpha.variance | alpha.2.5 | alpha.97.5 | a | a.2.5 | a.97.5 | b | b.2.5 | b.97.5 | c | c.2.5 | c.97.5 | d | d.2.5 | d.97.5 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 211 | Northeastern Mixed Forest | east | 6877 | 2876 | 1.0519043 | 0.0829277 | 0.4873898 | 1.6164188 | 0.0061791 | 0.0000347 | -0.0053718 | 0.0177299 | 0.8362509 | 0.0014948 | 0.7604605 | 0.9120413 | 0.5044588 | 0.4148313 | 0.5940863 | 1.8447001 | 1.6528388 | 2.036561 | 68.86977 | 66.41267 | 71.32687 | 0.9743399 | 0.9001357 | 1.048544 |
| 212 | Laurentian Mixed Forest | east | 22715 | 9499 | 1.0834155 | 0.0485461 | 0.6515456 | 1.5152854 | 0.0368214 | 0.0000180 | 0.0285051 | 0.0451377 | 1.0420658 | 0.0007219 | 0.9894021 | 1.0947295 | 0.3012473 | 0.2738593 | 0.3286353 | 1.3513096 | 1.2571637 | 1.445456 | 61.26196 | 59.66957 | 62.85435 | 1.0236589 | 0.9841957 | 1.063122 |
| 221 | Eastern Broadleaf Forest | east | 7333 | 3571 | -0.7623894 | 0.0219916 | -1.0530923 | -0.4716864 | 0.0152547 | 0.0000342 | 0.0037924 | 0.0267170 | 0.8462383 | 0.0017698 | 0.7637711 | 0.9287054 | 0.9526626 | 0.5895988 | 1.3157264 | 3.0453393 | 2.6393007 | 3.451378 | 62.84287 | 57.63040 | 68.05534 | 1.5038627 | 1.2775867 | 1.730139 |
| 222 | Midwest Broadleaf Forest | east | 5845 | 2589 | -0.0817463 | 0.0796215 | -0.6349338 | 0.4714411 | 0.0283120 | 0.0001195 | 0.0068811 | 0.0497428 | 0.9950652 | 0.0024354 | 0.8983177 | 1.0918127 | 0.6115125 | 0.5011758 | 0.7218492 | 2.3041529 | 2.0613073 | 2.546998 | 63.30978 | 60.04427 | 66.57528 | 1.0564370 | 0.9603756 | 1.152498 |
| 223 | Central Interior Broadleaf Forest | east | 10010 | 3864 | -0.8037980 | 0.0188709 | -1.0730783 | -0.5345176 | 0.0000000 | 0.0000508 | -0.0139675 | 0.0139675 | 0.7573656 | 0.0019477 | 0.6708546 | 0.8438766 | 0.8535710 | 0.5146840 | 1.1924580 | 2.4417317 | 2.0843858 | 2.799078 | 50.68180 | 48.30444 | 53.05916 | 1.3026110 | 1.1259027 | 1.479319 |
| 231 | Southeastern Mixed Forest | east | 13517 | 6193 | 1.6059080 | 0.0640245 | 1.1099317 | 2.1018843 | 0.0140402 | 0.0000334 | 0.0027140 | 0.0253664 | 0.9446226 | 0.0006482 | 0.8947175 | 0.9945277 | 0.4789238 | 0.4168518 | 0.5409959 | 3.1665610 | 2.9149967 | 3.418125 | 34.28951 | 33.27389 | 35.30513 | 1.2750921 | 1.2228990 | 1.327285 |
| 232 | Outer Coastal Plain Mixed Forest | east | 13629 | 6626 | 1.1397371 | 0.0604051 | 0.6579838 | 1.6214904 | 0.0198812 | 0.0000372 | 0.0079208 | 0.0318415 | 0.9639789 | 0.0006240 | 0.9150165 | 1.0129413 | 0.4112567 | 0.3416138 | 0.4808997 | 3.0296240 | 2.7750453 | 3.284203 | 32.68002 | 31.64702 | 33.71301 | 1.3089545 | 1.2504079 | 1.367501 |
| 234 | Lower Mississippi Riverine Forest | east | 1388 | 778 | -0.9771746 | 0.3414432 | -2.1234982 | 0.1691490 | 0.0990410 | 0.0012636 | 0.0293062 | 0.1687758 | 0.9155910 | 0.0146047 | 0.6785114 | 1.1526707 | 1.3388700 | 0.7554249 | 1.9223150 | 3.6678550 | 2.4312332 | 4.904477 | 42.96174 | 35.52629 | 50.39719 | 1.1091545 | 0.7546573 | 1.463652 |
| 242 | Pacific Lowland Mixed Forest | pacific | 83 | 83 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 251 | Prairie Parkland (Temperate) | east | 2295 | 906 | 0.9916487 | 0.3700369 | -0.2014252 | 2.1847225 | 0.0026890 | 0.0001558 | -0.0217893 | 0.0271673 | 0.4941728 | 0.0107199 | 0.2911053 | 0.6972402 | 0.7503314 | 0.4231671 | 1.0774957 | 1.3544657 | 0.9531469 | 1.755785 | 55.23233 | 50.06255 | 60.40211 | 1.1179190 | 0.8451422 | 1.390696 |
| 255 | Prairie Parkland (Subtropical) | east | 717 | 319 | 3.8979749 | 24.6266523 | -5.8461030 | 13.6420527 | 0.1663586 | 0.0035071 | 0.0500771 | 0.2826400 | 0.2273884 | 0.1425695 | -0.5140094 | 0.9687862 | 0.1502383 | -0.0291782 | 0.3296547 | 1.0321300 | -0.1664488 | 2.230709 | 29.91856 | 24.48669 | 35.35043 | 0.8752194 | 0.5781515 | 1.172287 |
| 261 | California Coastal Chaparral Forest and Shrub | pacific | 25 | 25 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 262 | California Dry Steppe | pacific | 0 | 0 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 263 | California Coastal Steppe - Mixed Forest and Redwood Forest | pacific | 163 | 161 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 313 | Colorado Plateau Semi-Desert | interior west | 218 | 218 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 315 | Southwest Plateau and Plains Dry Steppe and Shrub | interior west | 4 | 4 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 321 | Chihuahuan Semi-Desert | interior west | 9 | 9 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 322 | American Semidesert and Desert | interior west | 3 | 3 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 331 | Great Plains/Palouse Dry Steppe | interior west | 331 | 255 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 332 | Great Plains Steppe | interior west | 232 | 128 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 341 | Intermountain Semi-Desert and Desert | interior west | 66 | 64 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 342 | Intermountain Semi-Desert | interior west | 124 | 123 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| 411 | Everglades | east | 96 | 63 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M211 | Adirondack-New England Mixed forest - Coniferous Forest - Alpine Meadow | east | 6772 | 3006 | 1.5307098 | 0.1189068 | 0.8547368 | 2.2066828 | 0.0214535 | 0.0000344 | 0.0099480 | 0.0329589 | 0.8220032 | 0.0012938 | 0.7514927 | 0.8925136 | 0.2565489 | 0.1876879 | 0.3254099 | 1.7152006 | 1.5123176 | 1.918084 | 74.55799 | 71.17509 | 77.94089 | 1.0855416 | 1.0086953 | 1.162388 |
| M221 | Central Appalachian Broadleaf Forest - Coniferous Forest - Meadow | east | 8315 | 3810 | 1.1733507 | 0.0760512 | 0.6327646 | 1.7139367 | 0.0000000 | 0.0000462 | -0.0133202 | 0.0133202 | 0.9059893 | 0.0032884 | 0.7935800 | 1.0183986 | 0.6728062 | 0.3541398 | 0.9914726 | 2.3436378 | 1.9690490 | 2.718227 | 47.55626 | 45.22266 | 49.88986 | 1.3743578 | 1.1958064 | 1.552909 |
| M223 | Ozark Broadleaf Forest Meadow | east | 896 | 349 | 4.2321262 | 6.6624426 | -0.8338274 | 9.2980798 | 0.0000000 | 0.0008730 | -0.0579882 | 0.0579882 | 1.0089721 | 0.0301655 | 0.6680934 | 1.3498508 | 0.0000000 | -0.4934201 | 0.4934201 | 1.3190443 | 0.4387343 | 2.199354 | 42.48170 | 37.04414 | 47.91925 | 1.2773344 | 0.7792114 | 1.775457 |
| M231 | Ouachita Mixed Forest | east | 1006 | 495 | 3.3995885 | 6.6235564 | -1.6508274 | 8.4500044 | 0.0563340 | 0.0009892 | -0.0053865 | 0.1180546 | 0.8257426 | 0.0185220 | 0.5586721 | 1.0928130 | 0.0000000 | -0.6593637 | 0.6593637 | 1.3657568 | 0.3106896 | 2.420824 | 46.69611 | 34.99727 | 58.39496 | 1.7543539 | 0.8980146 | 2.610693 |
| M242 | Cascade Mixed Forest | pacific | 3224 | 3207 | -1.6901211 | 0.0809302 | -2.2479122 | -1.1323300 | 0.0199631 | 0.0003393 | -0.0161533 | 0.0560795 | 1.0765993 | 0.0051881 | 0.9353713 | 1.2178273 | 0.0000000 | -4.1913051 | 4.1913051 | 6.2319169 | 1.9545535 | 10.509280 | 94.67459 | 81.26815 | 108.08103 | 2.4754690 | 1.3046649 | 3.646273 |
| M261 | Sierran Steppe - Mixed Forest - Coniferous Forest - Alpine Meadow | pacific | 1977 | 1807 | -2.0018515 | 0.0862282 | -2.5778061 | -1.4258969 | 0.1975535 | 0.0002627 | 0.1657656 | 0.2293413 | 0.8507713 | 0.0111676 | 0.6434979 | 1.0580446 | 2.9379945 | -1.1328545 | 7.0088436 | 4.9500868 | 0.9422226 | 8.957951 | 49.61092 | 33.04772 | 66.17411 | 1.7770464 | 0.4490395 | 3.105053 |
| M262 | California Coastal Range Coniferous Forest - Open Woodland - Shrub - Meadow | interior west | 30 | 26 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
| M313 | Arizona-New Mexico Mountains Semi-Desert - Open Woodland - Coniferous Forest - Alpine Meadow | interior west | 367 | 367 | -2.5049581 | 0.1070130 | -3.1482929 | -1.8616232 | 0.0530004 | 0.0009206 | -0.0066699 | 0.1126706 | 0.5683921 | 0.0264132 | 0.2487753 | 0.8880088 | 0.0000000 | -4.2005688 | 4.2005688 | 3.5972300 | -0.8084094 | 8.002869 | 67.83177 | 41.83426 | 93.82927 | 1.6609659 | -0.0974751 | 3.419407 |
| M331 | Southern Rocky Mountain Steppe - Open Woodland - Coniferous Forest - Alpine Meadow | interior west | 1756 | 1756 | 0.6242463 | 1.3501290 | -1.6547405 | 2.9032331 | 0.0832436 | 0.0002495 | 0.0522604 | 0.1142268 | 0.7659065 | 0.0035748 | 0.6486378 | 0.8831753 | 0.4840268 | 0.2510241 | 0.7170294 | 0.7603507 | 0.4126472 | 1.108054 | 82.23818 | 72.79446 | 91.68190 | 0.8901647 | 0.6921241 | 1.088205 |
| M332 | Middle Rocky Mountain Steppe - Coniferous Forest - Alpine Meadow | interior west | 2612 | 2602 | -0.8380746 | 0.2593952 | -1.8367876 | 0.1606385 | 0.0556339 | 0.0003276 | 0.0201397 | 0.0911282 | 0.9500686 | 0.0031481 | 0.8400461 | 1.0600911 | 0.5122166 | 0.3404392 | 0.6839940 | 2.1138072 | 1.5387742 | 2.688840 | 89.98718 | 82.08404 | 97.89032 | 1.2454840 | 1.1000550 | 1.390913 |
| M333 | Northern Rocky Mountain Steppe - Coniferous Forest - Alpine Meadow | interior west | 1753 | 1742 | 0.8444638 | 1.5981707 | -1.6350968 | 3.3240245 | 0.0082270 | 0.0004908 | -0.0352237 | 0.0516778 | 0.9774818 | 0.0037352 | 0.8576093 | 1.0973544 | 0.4652640 | 0.2414740 | 0.6890540 | 2.3672043 | 1.2764546 | 3.457954 | 63.95987 | 60.25779 | 67.66195 | 1.0829957 | 0.9911111 | 1.174880 |
| M334 | Black Hills Coniferous Forest | interior west | 459 | 181 | -1.1951946 | 2.0101417 | -3.9837191 | 1.5933299 | 0.0000000 | 0.0020037 | -0.0880392 | 0.0880392 | 0.6865993 | 0.0281345 | 0.3567005 | 1.0164981 | 0.0000000 | -15.4403982 | 15.4403982 | 1.4053800 | -13.9807277 | 16.791488 | 125.20338 | -114.37826 | 364.78503 | 2.5030610 | -16.2806247 | 21.286747 |
| M341 | Nevada-Utah Mountains Semi-Desert - Coniferous Forest - Alpine Meadow | interior west | 220 | 220 | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA |
plot ge
map
## OGR data source with driver: ESRI Shapefile
## Source: "C:\Users\hogan.jaaron\Dropbox\FIA_R\Mapping\S_USA.EcoMapProvinces\S_USA.EcoMapProvinces.shp", layer: "S_USA.EcoMapProvinces"
## with 37 features
## It has 17 fields
## Integer64 fields read as strings: PROVINCE_ PROVINCE_I## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, : font
## family not found in Windows font database
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, : font
## family not found in Windows font database
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, : font
## family not found in Windows font database
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, : font
## family not found in Windows font database
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, : font
## family not found in Windows font database
## Warning in grid.Call(C_textBounds, as.graphicsAnnot(x$label), x$x, x$y, : font
## family not found in Windows font database
plot phi (effect of DeltaPDSI)
plot alpha (biomass growth compensation effect)
plot a coefficient
## Warning: Removed 15 rows containing missing values (geom_point).
plot b coefficient
## Warning: Removed 15 rows containing missing values (geom_point).
plot c coefficient
## Warning: Removed 1 rows containing missing values (geom_hline).## Warning: Removed 19 rows containing missing values (geom_point).
plot d coefficient
## Warning: Removed 15 rows containing missing values (geom_point).
Caclulations - weighted averages
ge (stand biomass growth enhancement factor in % 2000-2021)
## region weighted.ge weighted.ge.std_Error 95 % CI, upper 95 % CI, lower
## 1 entire US 0.49375055 0.09590657 0.68172742 0.3057737
## 2 pacific -0.15602182 0.01822046 -0.12030973 -0.1917339
## 3 east 0.66270439 0.07505051 0.80980338 0.5156054
## 4 interior west -0.01293202 0.05686392 0.09852127 -0.1243853phi (effect of DeltaPDSI)
## region weighted.phi weighted.phi.std_Error 95 % CI, upper
## 1 entire US 0.029083247 0.002342738 0.033675014
## 2 pacific 0.007268032 0.001138258 0.009499018
## 3 east 0.016209381 0.001673911 0.019490246
## 4 interior west 0.005605834 0.001179328 0.007917317
## 95 % CI, lower
## 1 0.024491479
## 2 0.005037046
## 3 0.012928516
## 4 0.003294351alpha (biomass growth compensation effect)
## region weighted.alpha weighted.alpha.std_Error 95 % CI, upper
## 1 entire US 0.89468262 0.011392574 0.91701207
## 2 pacific 0.08614584 0.005174041 0.09628696
## 3 east 0.70749824 0.009416443 0.72595447
## 4 interior west 0.10103855 0.003788224 0.10846347
## 95 % CI, lower
## 1 0.87235318
## 2 0.07600472
## 3 0.68904201
## 4 0.09361363